BootNext

The platform provides software utilities designed to Analyse, Process and Extract the information from an extremely complex and large data sets which the Traditional Data Processing Software could never deal with

A big data platform for both IT and the business:

• Simple to use and secure by design
• Manual and automated
• Open and extensible
• For data engineers and data scientists
• On premises and public cloud

Hybrid & multi-cloud

Operates across all major public clouds and the private cloud with a public cloud experience everywhere

Multi-function analytics

Integrates big data management and analytic experiences across the data lifecycle for data anywhere

Secure & governed

Delivers security, compliance, migration, and metadata management across all environments

Open platform

Open source, open integrations, extensible, & open to multiple data stores and compute architectures

• Data Ingestion, Management, ETL, and Warehouse – It provides these resources for effective data management and effective data warehousing, and this manages data as a valuable resource.
• Stream Computing – Helps compute the streaming data that is used for real-time analytics
• Analytics/ Machine Learning – Features for advanced analytics and machine learning.
• Integration – It provides its user with features like integrating big data from any source with ease.
• Data Governance – It also provides comprehensive security, data governance, and solutions to protect the data.
• Provides Accurate Data – It delivers with analytic tools which in turn helps to omit any inaccurate data that has not been analysed. This also helps the business to make the right decision by utilizing accurate information
• Scalability – It also helps scale the application to analyse all time climbing data; it sizes to provide efficient analysis. It offers scalable storage capacity.
• Price Optimization – Data analytics with the help of a big data platform provides insight for B2C and B2B enterprises which helps the business to optimize the prices they charge accordingly.
• Reduced Latency – With the set of the warehouse, analytics tools, and efficient Data transformation, it helps to reduce the data latency and provide high throughput

Bring all your data together with a data lake

Complete, integrated solution

Deploy a complete, integrated solution, including data management, data integration, and data science, so analytics teams can maximize the value of enterprise data. Customers ingest any data via batch, streaming, or real-time processes and store it in data warehouses or data lakes as needed. Teams then catalog and apply governance to the data so they can use it for analyses, visualizations, and machine learning models. IT teams leverage consistent security policies across data warehouses and data lakes.

Easy to manage and operate

Increase developer productivity with a fully managed, serverless, Apache Spark cluster that is accessible via APIs. Each cluster is automatically provisioned, secured, and shut down to reduce developer workloads. Customers can deploy fully managed Hadoop clusters of any size or shape, then add security and high availability with a single click.

Cloud Data services

• DATA HUB: Simplify building mission-critical data-driven applications with security, governance, scale, and control across the data lifecycle
• DATA WAREHOUSE: Unleash hybrid and multi-cloud data warehouse service for all modern, self-service, and advanced analytics use cases, at scale
• MACHINE LEARNING: Accelerate development at scale, anywhere, with self-service machine learning workspaces and the underlying compute clusters
• DATA ENGINEERING: Orchestrate, operationalize, and automate complex data pipelines to increase efficiency and accelerate time to value
• DATA VISUALIZATION: Curate and deliver rich, visual dashboards and applications that accelerate operationalization of analytical insight across your enterprise
• OPERATIONAL DATABASE: Bring unparalleled scale and performance to your mission-critical applications while securing future readiness for evolving data models